In the operation at so-called contact center and call center which handle various inquiries and claims made to companies from customers related to products and services, there come numbers of inquires related to estimation and order of products and services, after-services and repairs every day. For an operator to answer to such an inquiry, it is very useful to prepare a collection of questions/answers generally called FAQ or QA collection in advance.
By properly referring to such a collection of questions and answers according to the content of an inquiry from a customer, an operator answering to the inquiry is allowed to make an appropriate response efficiently. In addition, since displaying a question/answer collection such as FAQ or QA collection on a home page of a corporate enables customers to solve their own problems by checking the question/answer collection, the number itself of direct inquiries by a call or mail is expected to be reduced.
Also for such operation of actually attending to a customer face to face as sales and reception, it is essential to prepare examples of responses to assumed inquiries or an attendance manual as a list of points to be noted regarding some kinds of questions. These attendance manuals can be used not only at the time of actual attendance to customers but also for training attendant operators.
Collections of questions/answers used at a contact center or a call center and attendance manuals used in sales and reception are here assumed to be data having basically the same kind of structure. These data include a question part indicative of contents and contexts of questions/inquiries and an answer part indicative of a manner of answering and points to be noted thereto. In the present specification, data edited premised on reuse will be referred to as question and answer data.
When generating such question and answer data as described above, in addition to preparation of questions and answers of abundant contents coping with various situations, it is also essential to generate an index for search such that generated question and answer data can be searched and referred to with ease.
Among techniques as related art in association with generation of these questions and answers data are, for example, Japanese Patent Laying-Open No. 11-272584 (Literature 1), Japanese Patent Laying-Open No. 2003-30224 (Literature 2) and Japanese Patent Laying-Open No. 2003-223460 (Literature 3).
Literature 1 discloses a technique targeting questions made by electronic mail to a home page on the Internet. According to this related art, together with a question of a person who browses a home page, context data indicative of a context in which a question was asked and user data indicative of an attribute of a person who browses are collected and accumulated in a data base. This enables, for example, such information as what kind of person he is who browses and with which page, the person asked a question to be found for use in improving a home page.
Also disclosed is a method of creating a QA collection on a page or date basis by sorting accumulated contents of questions on a page or date basis and generating an answer to them by an operator at the time of creating a QA collection.
Disclosed in Literature 2 is a technique for classifying a set of accumulated pairs of documents of questions and documents of answers into several non-hierarchical clusters. According to the technique, generating clusters by putting similar documents from numbers of question/answer documents together and selecting a typical question/answer document from each cluster enables use for FAQ preparation. In addition, outputting only a typical document of each cluster at the time of search of a question/answer document helps listing of search results to improve.
Literature 3 discloses a technique of holding expressions predicted to be used in customers' inquiries in linkage with their associated searching key words. To a searching key word “clogging” of a printer, for example, such expressions as “no ink fed” and “lines thin” are linked. This enables a QA collection related to “clogging” of a printer to be searched immediately when an inquiry whose content is “no ink fed” is actually made by a customer.
The above-described related art has the following problems.
First problem is that when generating question and answer data such as FAQ, no details are known of expressions actually used by a customer and a context/condition in which an individual question/inquiry is made.
Although when generating question and answer data, reports of the contents of answers actually made by an operator in response to an inquiry from a customer or records of experience contents are in general used, many of these reports/records are summary of contents of actual inquires and answers and not raw data. Therefore, in a case of a question whose content is of the same kind and which has many variations according to expressions used by a customer, such a situation can not be found from the reports/records. In addition, although questions/inquiries have their own contexts/conditions in which they are made and there are a case where an answer to the same question may vary with such contexts/conditions and a case where later reaction or selection of a customer in response to an answer may vary, it is difficult to determine such a context/condition from reports/records.
In the method of displaying accepted inquiry mail on a home page disclosed in Literature 1, situations in which inquires were made are accumulated in pair with the inquires. Target of this technique is only inquiry mail occurring when a home page is browsed and as to a situation in which an inquiry occurs, information is limited to user profile, time and date of an inquiry and a page browsed when the inquiry was made.
Disclosed in Literature 2 is a technique of putting accumulated documents of questions and documents of answers into a plurality of clusters which are highly similar to each other. Accordingly, when the clustering works well, checking documents belonging to the same cluster leads to checking expression variations whose contents are of the same kind. In general, however, clustering techniques fail to work effectively unless such conditions as formats and lengths of documents are uniform. Therefore, in a case where one question document is very short and the other question document is long and has a plurality of questions, even when they include questions of the same kind, they are not always grouped into the same cluster. Neither a context nor a condition where a question was made is found by the technique of Literature 2.
In the information provision supporting system disclosed in Literature 3, such expressions actually used by customers as “no ink fed” and “line thin” and a searching key word “clogging” are linked in advance and used at the time of searching a QA collection. This is equivalent to handling expression variations of the searching key word “clogging”. It is still yet to be solved how expressions actually used by customers and expressions used in a QA collection (searching key words) are collected and how to make a determination which expression should be appropriately linked with which searching key word.
Second problem is unclearness of relationships between a plurality of question and answer data.
There often occur a case where a plurality of questions are made in a set or in series such as a case where a customer makes a plurality of inquires once and a case where a customer having made a question receives an answer to it and then makes a further question. In such a case, for creating a data base of question and answer data such as an FAQ based on such questions and inquiries, it is desirable not to accumulate data as individual question and answer data but to index the respective question and answer data as associated questions and answers. If the data is indexed as associated questions and answers, when actually attending to a customer, an operator, after searching by one question and answer, is allowed to prepare before the customer actually makes an inquiry while looking at associated questions and answers, or present information about associated questions and answers to the customer from the side of the operator before customer's asking. In addition, at the time of publicizing question and answer data as FAQ on a home page or the like, putting related question and answer data together or displaying them as a link improves browsing facility.
The related art, however, is yet to present a method of efficiently extracting a relationship between these individual question and answer data.
A first exemplary object of the present invention is to solve these problems, and to provide a question and answer data editing device capable of generating question and answer data and index information by extracting an expression pattern including a context/condition related to question and answer data or an expression variation of question and answer data from data of a history of dialogues made in the past between operators and customers, and an editing method and a program thereof.
A second exemplary object of the present invention is to provide a question and answer data editing device capable of detecting contents of a dialogue similar to question and answer data from data of a history of dialogues made in the past between operators and customers and correlating the detected contents with original question and answer data, and an editing method and a program thereof.